With the development of the Internet in the world, there are more and more people accepting the Internet and relying on the Internet for their work and daily lives. Activities previously requiring face to face interaction are gradually being replaced by the Internet.
The development of the Internet has generated a variety of applications, one of which is electronic commerce, i.e., e-commerce.
E-commerce utilizes computer technology, network technology, and remote communicating technology to achieve electronics, digitalization, and networking for the entire transaction process. The term e-commerce is usually referred to as a novel business model by which worldwide commercial and trade activities are transacted in an open network environment such as the Internet. In e-commerce, various commercial and trade activities, such as on-line shopping by a consumer, on-line transactions between merchants, on-line payment as well as all kinds of business activities, trade activities, financial activities and related activities of integrated services are conducted based on the application of browsers/servers, where a face to face meeting between a buyer and a seller is not required.
With the development of e-commerce, there are more and more consumers, i.e., users, choosing to purchase various products and services such as clothes, digital products, home appliances, books and lottery tickets online. However, it is not easy for a user to choose the most satisfying item from a wide range of products and services on the Internet, especially when the transaction is made when the user cannot see the physical object or is unfamiliar with the merchant.
There are a lot of websites that provide information related to products and services to help the user make a decision, among which the most convenient and effective one is offering the comments provided by other users with respect to these products or services. Accordingly, the user can make his/her decision based on a massive amount of comments about the product or the service from a massive amount of other users.
A comment search engine based on user comments is a key solution for resolving this issue. When the user clicks a product or a product attribute on a webpage, the comment search engine will perform a search in an index file according to a keyword, and return the most relevant comment information.
However, as a number of comments with respect to the desired product or the desired service may be large, the user may not have sufficient time or energy to read through all the comments. Thus, how the user can rapidly and efficiently retrieve a helpful comment that facilitates decision making has become a problem.
In addition, such commenting platforms are open to the users. In other words, the contents of the comments are not restricted. Consequently, a lot of spam contents such as advertisements, contents irrelevant to the product, or contents with very little useful information may be contained in the growing massive amount of comments with respect to the product. Thus, how to help the user to effectively eliminate or ignore the comments containing spam contents has also become an issue.
The conventional techniques solve these issues by ranking the comments in accordance with time. Specifically, the most recent comment is displayed at the top, and the earlier comment is displayed at the bottom. In this way, the most recent comment can be read by the user in his first priority, and the comments that are published earlier will be read in a low priority as the user scrolls down the page or flips the page.
However, users usually become impatient in the operation of flipping the list of pages during the browsing process. Prior experiences show that users often start to leave the page when the users begin to browse the third page, and a proportion of users leaving the page become higher as the number of pages browsed increases.
Therefore, an excellent content published earlier that is helpful to the user's decision making may be unread by the user. Accordingly, the conventional sorting method that only considers a sequence of publishing time cannot help the user to quickly reach high quality content, and is not helpful for reducing the time of decision making for the user.
Moreover, sometimes the user may not want to browse each comment one by one, but rather wants to focus on reading comments with respect to a specific attribute or a specific aspect of the product or the service. Such a demand may be satisfied by performing an emotional analysis of the comments.
The emotional analysis of the comment is referred to performing a structural analysis with respect to the content of the comment so as to obtain a description of the overall product and attributes in each dimension expressed by the users through their comments.
Therefore, the present techniques efficiently provide good quality and useful comment contents to the user and reduce a number of pages that the user flips.